Leveraging e-Science infrastructure for electrochemical research

Abstract

As in many scientific disciplines, modern chemistry involves a mix of experimentation and computer-supported theory. Historically, these skills have been provided by different groups, and range from traditional 'wet' laboratory science to advanced numerical simulation. Increasingly, progress is made by global collaborations, in which new theory may be developed in one part of the world and applied and tested in the laboratory elsewhere. e-Science, or cyber-infrastructure, underpins such collaborations by providing a unified platform for accessing scientific instruments, computers and data archives, and collaboration tools. In this paper we discuss the application of advanced e-Science software tools to electrochemistry research performed in three different laboratoriestwo at Monash University in Australia and one at the University of Oxford in the UK. We show that software tools that were originally developed for a range of application domains can be applied to electrochemical problems, in particular Fourier voltammetry. Moreover, we show that, by replacing ad-hoc manual processes with e-Science tools, we obtain more accurate solutions automatically.

Models and Their Limitations in the Voltammmetric Parameterization of the Six‐Electron Surface‐Confined Reduction of [PMo12O40]3− at Glassy Carbon and Boron‐Doped Diamond Electrodes

“…In recent work, the Oxford Computing and Monash University Electrochemistry Groups have been developing protocols that reliably and efficiently parameterize complex electrochemical processes (see [6][7][8][9] for example). In summary, very large data sets containing current, potential, and time domain information are collected [6][7][8][9] at high resolution using instrumentation having 18 bit DAC and ADC converters.…”

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

“…As an alternative to the fully heuristic method, multi‐parameter fitting aided by computationally efficient data optimization or more sophisticated approaches are now available to assist with solving the inverse problem in voltammetry ,. Data optimization methodology, underpinned by statistics and facilitated by high speed computing, has been developed to support many branches of science.…”

“…As an alternative to the fully heuristic method, multiparameter fitting aided by computationally efficient data optimization or more sophisticated approaches are now available to assist with solving the inverse problem in voltammetry. [8,[10][11][12][13][14][15][16][17][18] Data optimization methodology, underpinned by statistics and facilitated by high speed computing, has been developed to support many branches of science. Now, just as there are many voltammetric simulation packages available for modelling the forward problem, there is an extensive range of software packages available to support complex theory-experiment data optimization exercises.…”

Limitations in Electrochemical Determination of Mass-Transport Parameters: Implications for Quantification of Electrode Kinetics Using Data Optimisation Methods

“…In particular, the current magnitude in a.c. harmonics of a Fourier-transformed (FT) a.c. voltammogram depends on all these parameters and propagation of errors can occur. In the present paper, the consequences of errors in the mass-transport parameters (A, D, c) on the quantification of the electrode kinetics on the basis of the voltammetric experimenttheory comparisons are explored with a computer-aided method of data analysis [6,8,11,12] applied to recover the parameters relevant to the quasi-reversible process given in Reaction 1.…”